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Risanuri Hidayat
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Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada Jl. Grafika No 2. Kampus UGM Yogyakarta 55281
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Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Published by Universitas Gadjah Mada
ISSN : 23014156     EISSN : 24605719     DOI : 10.22146/jnteti
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering
Topics cover the fields of (but not limited to): 1. Information Technology: Software Engineering, Knowledge and Data Mining, Multimedia Technologies, Mobile Computing, Parallel/Distributed Computing, Artificial Intelligence, Computer Graphics, Virtual Reality 2. Power Systems: Power Generation, Power Distribution, Power Conversion, Protection Systems, Electrical Material 3. Signals, Systems, and Electronics: Digital Signal Processing Algorithm, Robotic Systems and Image Processing, Biomedical Instrumentation, Microelectronics, Instrumentation and Control 4. Communication Systems: Management and Protocol Network, Telecommunication Systems, Wireless Communications, Optoelectronics, Fuzzy Sensor and Network
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 12 Documents
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Search results for , issue "Vol 7 No 4: November 2018" : 12 Documents clear
Fair Assessment pada Kolaborasi Pemodelan Persyaratan Perangkat Lunak UML Danang Wahyu Utomo; Egia Rosi Subhiyakto; Defri Kurniawan
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 4: November 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1266.838 KB)

Abstract

In software engineering education, students are expected to be able to collaborate with other student in team project. Based on the RPS and Software Engineering syllabus, student must be able to create SRS document in group assignment. In general, lecturers assess students based on team cohesiveness, student accuracy in answering questions, and final result of SRS documents. The weakness of the assessment model is that the lecturer cannot know student who are really active and contribute to the team. Student will get the same marks. There is no difference in marks between active and passive students. The impact, active student can become passive, because the result obtained in the presentation of final assignment is no different from the other student. It can make student contribution decrease. Student are reluctant to group in completing their final assignments. This paper aims to propose a fair assessment approach to provide an assessment that is appropriate to the composition of group assignment. Fair assessment consists of assignment component, diagram modeling, and final project. In addition, re-implementation was carried out on the previous collaborative tool by replacing the assessment model and adding some features such as friend search menu and real time discussion. The evaluation involved 55 students majority in Software Engineering to test fair assessment approach and new features of collaboration tool. The result shows that students agree that a fair assessment approach is appropriate to be used in supporting collaborative software engineering education, especially UML diagram modeling.
Penentuan Kualitas Air untuk Perkembangan Ikan Lele Sangkuriang Menggunakan Metode Fuzzy SAW Dony M Sihotang
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 4: November 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

The purpose of this paper is to implement Fuzzy Simple Additive Weighting (F-SAW) method in determination of water quality for the development of Sangkuriang catfish, using six criteria, i.e. temperature, pH, DO, brightness, plankton, and odor, using 15 alternatives (pool). There are two test scenarios that have been done in this research to obtain system accuracy level, which are: 1) result of system compared with assessment from an expert; and 2) the results of the system compared with assumption of the study that the alternative with the best data should be ranked first and the alternative with the worst data should be rated last. The results obtained from the first scenario shows the level of accuracy is 87%, while the results obtained from the second scenario shows 100% accuracy rate.
Analisis Constructivist Multimedia Learning Environment dengan Pendekatan Bayesian Structural Equation Model Eny Sukani Rahayu; Adhistya Erna Permanasari; Dewa Ayu Putu Nadya Hareswary; Inas Ulfah Prisabtini
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 4: November 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1511.263 KB)

Abstract

Constructivist Multimedia Learning Environment (CMLE) is a learning model where the teacher gives the student an experience that can help them to develop high order thinking skills such as critical thinking, developing solutions, and be creative around their environment. CMLE uses multimedia as their main source of information and as a tool to deliver learning materials. For that purpose, evaluation is needed to assess the effectiveness of the learning model. This evaluation is known as CMLE Survey (CMLES). Data obtained from CMLES needs to be analysed using analytical methods that can show the relationship between each variable and the indicator. Bayesian Structural Equation Model (SEM) is considered as the right approach because of many advantages of Bayesian Approach, such as using prior information to get posterior result and not affected by the number of samples. The seven existing hypotheses are accepted with the following results. RTH has a positive influence on CHL while CHL has a positive effect on COM. RLV has a positive influence on COM. RTH has a positive influence on INQ while INQ has a positive influence on NEG. Nevertheless, CHL gives a negative influence on INQ and RLV gives a negative influence on CHL.
Rancang Bangun Identity and Access Management IoT Berbasis KSI dan Permissioned Blockchain Guntur Dharma Putra; Sujoko Sumaryono; Widyawan Widyawan
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 4: November 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1118.359 KB)

Abstract

Blockchain offers several technological break-throughs, ranging from monetary solutions to healthcare systems. Some approaches have proposed blockchain implementation in IoT for providing better performance and scalability. However, massive scale implementation of IoT devices suffers from several issues in identity and access managements of interconnected devices. The present study proposes the combination of permissioned blockchain and Keyless Signature Infrastructure (KSI) as a means of governing the identity and access management of IoT devices. KSI is known for its ability to offer digital signature services without the need of public or private key but hash trees updated in a regular basis. With the decentralization fashion of blockchain, KSI can be implemented more efficiently. The results may give an identity and access management with high scalability.
Pemantauan dan Pengendalian Kepekatan Larutan Nutrisi Hidroponik Berbasis Jaringan Sensor Nirkabel Helmy Helmy; Aji Rahmawati; Syahrul Ramadhan; Thomas Agung Setyawan; Arif Nursyahid
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 4: November 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1208.613 KB)

Abstract

Nutrient Film Technique (NFT) is one of hydroponic plant cultivation models. Most of hydroponic farmers are using NFT model to raise the productivity of crops. NFT hydroponic farmers usually use more than one hydroponic table in order to fulfill market needs. Harvest failures can happen when farmers do not have suficient information on monitoring and controlling the nutrition solution concentration. This can be overcome with the existence of monitoring and controlling system of nutrition solution concentration. This paper aims to build and examine system reliability using two NFT hydroponic tables based on wireless sensor network. Each table is installed with monitoring and controlling of nutrition solution concentration devices which transmit the data to server throughwireless sensor network. The result shows that electrical conductivity meter which is used to read nutrition solution concentration has 3.92% of error rate. Node 2 has faster threshold data transmission than node 1, with 34.68 second of node 2 delay and 40.01 second of node 1 delay. Node 1 has better accuracy of nutrition solution concentration control for 96.12% than node 2 which has 92.79% nutrition solution concentration accuracy.
Deteksi Gestur Lengan Dinamis pada Lingkungan Virtual Tiga Dimensi Koleksi Warisan Budaya Adri Gabriel Sooai; Atyanta. N. Rumaksari; Khamid Khamid; Nurul Zainal Fanani; Surya Sumpeno; Mauridhi Hery Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 4: November 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Virtual reality technology can be used to support museum exhibitions. Implementation could be in various platforms. There are many implementation options, for example in smartphones, tablet, and desktop computers. Most objects of museum collections are very fragile. Minimizing the direct touch on a collection object is one of the benefits of this technology. This study aims to prepare gestures suitable for the exploration of virtual objects of cultural heritage collection. Five sets of gestures have been prepared, namely lifting, picking, holding, sweeping from both directions, left and right. Dynamic arm gestures are recorded using the forearm sensor. The recorded data contains coordinates of gestures in form of x, y, z, raw, pitch, and yaw. Gaussian mixture models are used in selecting features to produce good accuracy in the classification process.Two functions are used, namely probability density function and cumulative distribution function for the feature selection process. In this study, two experiments were used to train the gesture model. The accuracy of the two experiments is shown in the form of a confusion matrix. Each of the confusion matrices show excellent results of 99.8% for SVM and k-NN. Furthermore, modeling results are tested using new data. The testing shows 89.25% result for SVM classifier and 90.09% for k-NN. Four other dynamic arm gestures have a very satisfactory rate of 100% for the two classifiers. The five gestures can be used in the development of virtual reality applications.
Deteksi Limfoblas pada Citra Sel Darah Menggunakan Fitur Geometri dan Local Binary Pattern Annisaa Sri Indrawanti; Eka Prakarsa Mandyartha
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 4: November 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Lymphoblasts are white blood cell types of lymphocytes, which can mark leukemia. To identify lymphoblasts, an analysis of white blood cells is required. In this study, a computer-based automated system was proposed using digital image processing techniques to detect lymphoblasts by analyzing microscopic images of blood cells. This proposed method segments the components of white blood cells, which are cytoplasm and nucleus, using a new approach based on adaptive local thresholding techniques. After each cell component was segmented, the geometry features and texture were extracted. The texture feature used a local binary pattern (LBP) descriptor from the nucleus. The set of features was used to train the support vector machine classification algorithm in detecting lymphoblasts. The proposed method is able to segment correctly 264 of 269 total white blood cells, with 98.14% accuracy, out of 35 acute lymphoblastic leukemia images taken with the same camera with the same lighting conditions. The use of geometry features with 16 dimensional feature vector and LBP features with 256 dimensional feature vector result in accuracy of lymphoblast identification of 88.79% and 89.72% respectively. Better performance is obtained by combining two features, the geometry and the LBP with 272 dimensional feature vector, with classification accuracy of 94.32%.
Implementasi Sistem Notifikasi untuk Pengawasan Pasien Alzheimer Berbasis Bluetooth Low Energy (BLE) Aries Pratiarso; Trisna Agung Mahendra; Mike Yuliana; Prima Kristalina; I Gede Puja Astawa; Arifin Arifin
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 4: November 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Alzheimer's patients need attention and special treatment due to their inability to remember something. One technology that is widely used for tracking objects or people in an indoor environment is a Bluetooth Low Energy (BLE). In this paper, a surveillance notification system for Alzheimer's patients is proposed using Beacon technology to prevent the lossof patients. Improvement in accuracy of the estimated position of the patient were calculated using a Kalman filter. The reason for using this method was the difficulty of determining the location of objects due to noise and inaccuracy of measurement data.Fromthe results of the tests performed, it can be seen that the system made is able to provide notifications to nurses if the patient exceeds the specified distance with an average success of up to 90%. The use of the Kalman method is also able to increase the accuracy of the estimation of patient position with an estimated error reduction of 69.7%.
Ekstraksi Ciri Produktivitas Dinamis untuk Prediksi Topik Pakar dengan Model Discrete Choice Diana Purwitasari; Chastine Fatichah; Surya Sumpeno; Mauridhi Hery Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 4: November 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Recommendation of active or productive experts is indispensable in supporting collaborations. Activities of publication and citation indicate expert productivity. An expert can be inferred to have an interest in a subject through productivity in that particular topic. Since an expert can change interests over time, the contribution of this paper is a Discrete Choice Model (DCM) based on topic productivities to predict the primary interests of the experts. DCM uses features extracted from bibliographic data of citation relation and title-abstract texts. Before extracting productivity features and dynamicity features to represent interest changes, title clustering with KMeans++ is used to identify research topics. There are six productivity features and five dynamicity values for each productivity feature to demonstrate the expert behavior. Therefore, a clustered topic as a research interest is represented as an expert choice with 30 extracted features in the proposed method. The experiments used multinomial logistic regression for DCM and a log-likelihood indicator for the fitted models of the features. The resulted DCM models showed that productive behavior of the experts by doing many publications and receiving many citations effected to the precision of topic prediction by 80%. Some features were better for predicting primary interests of the expert. It was demonstrated with a lower precision value of 60% by using features that represent the expert behavior of only doing publication or only getting citation.
Estimasi Rapat Spektral Daya Berbasiskan Compressive Sampling Dyonisius Dony Ariananda
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 4: November 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

This paper focus on spectrum sensing based on power spectral density (PSD) reconstruction from sub-Nyquist-rate samples. In the existing works on PSD reconstruction from sub-Nyquist-rate samples, the resulting system of linear equations (SLE) is generally overdetermined, which allows the PSD reconstruction using least-squares (LS). Note that there is a lower bound for the achievable sampling rate ensuring that the resulting SLE is overdetermined. This paper aims for a further sampling rate reduction, which results in an underdetermined SLE. However, when the resulting SLE is underdetermined, the LS method cannot be used to reconstruct PSD and additional constraints are required. Under this circumstance, a sparsity assumption (which is applicable for some applications) can be applied on the PSD. The use of the orthogonal matching pursuit (OMP) and the least absolute shrinkage and selection operator (LASSO) algorithms to reconstruct the PSD for the case of underdetermined SLE is examined. The simulation study shows that if an appropriate regularization parameter is used, the quality of the PSD reconstructed using LASSO is only slightly below the one produced using Nyquist-rate sampling. From the detection point of view, the PSD reconstructed using LASSO can accurately locate the occupied frequency band when the user signal power is sufficiently high compared to the noise power. Meanwhile, OMP can be used only in the noiseless scenario. These results indicate that the sampling rate alleviation up to a very low rate is possible while maintaining the quality of the spectrum sensing results at the acceptable level.

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